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Christoph Baumgarten

dblp:63/1152 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 2000
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 3 · 3 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
2 papers
Information retrieval · 83% Data mining · 17%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
distributed information retrieval		 0.021999
A Probabilitstic Solution to the Selection and Fusion Problem in Distributed Information Retrieval · SIGIR 1999
A Probabilistic Model for Distributed Information Retrieval · SIGIR 1997
Information retrieval › distributed information retrieval
resource selection		 0.011999
A Probabilitstic Solution to the Selection and Fusion Problem in Distributed Information Retrieval · SIGIR 1999
Information retrieval › distributed information retrieval
result fusion		 0.011999
A Probabilitstic Solution to the Selection and Fusion Problem in Distributed Information Retrieval · SIGIR 1999
Data mining
probabilistic model		 0.011997
A Probabilistic Model for Distributed Information Retrieval · SIGIR 1997

Methods — techniques the papers use, named apart from their topics

probability ranking principle · 0.0
YearPublicationVenuePosition
2000 Retrieving Information from a Distributed Heterogeneous Document Collection
Christoph Baumgarten
 Inf. Retr.1
1999 A Probabilitstic Solution to the Selection and Fusion Problem in Distributed Information Retrieval
abstract
A model for optimal information retrieval over a distributed document collection is described and experimentally evaluated. The fusion of retrieval results corresponding to document subcollections is performed according to the Probability Ranking Principle. Part of the model is a selection criterion for effectively limiting the ranking process to a subset of subcollections. 1 Introduction An information retrieval (IR) system is a tool for searching information in a collection of documents that satisfies a user's information need. In order to use an IR system, the user has to formulate his or her information need; the resulting query is then taken by the system to rank the documents according to an estimate of their probabilities of being relevant to the user's information need. For this purpose, a corresponding ranking method is called with the query. It assigns retrieval status values (RSVs) to the documents. A document's RSV determines the position of the document in the ranked lis...
Christoph Baumgarten
 SIGIR1
1997 A Probabilistic Model for Distributed Information Retrieval
abstract
No abstract available.
Christoph Baumgarten
 SIGIR1
1997 Approximation of logarithmic spirals
Christoph Baumgarten, Gerald E. Farin
 Comput. Aided Geom. Des.1